It's not every day that an 18-year-old college student catches the eye of the computing world, but when Ewin Tang took aim at recommendation algorithms similar to those commonly used by the likes of Amazon and Netflix, the University of Texas at Austin mathematics and computer science undergraduate blew up an established belief: that classical computers cannot perform these types of calculations at the speed of quantum computers. In a July 2018 paper, which Tang wrote for a senior honors thesis under the supervision of computer science professor Scott Aaronson, a leading researcher in quantum computing algorithms, she discovered an algorithm that showed classical computers can indeed tackle predictive recommendations at a speed previously thought possible only with quantum computers. "I actually set out to demonstrate that quantum machine learning algorithms are faster," she explains. "But, along the way, I realized this was not the case." Ewin Tang set out to show that quantum machine learning algorithms are faster than classical algorithms, "but ... I realized this was not the case."

Someday, perhaps, streets and highways will host only fully autonomous vehicles, wirelessly communicating and following algorithms that let them handle any situation they encounter. For now, though, city streets are filled with pedestrians, bicyclists, delivery trucks, double-parked cars, emergency vehicles, and construction crews, as well as human-operated cars with issues of their own. In this chaotic setting, self-driving cars face additional challenges beyond rapidly analyzing the complex environment and navigating through it. They also must keep their distracted occupants informed of issues potentially requiring attention. Equally important, they must continually coordinate their actions with humans, whether in other cars or on the street.

On screen, the virtual character sits in a comfortable purple chair. She wears plain pants, a turquoise shirt, and a slim jacket with the sleeves rolled up past her elbows. Her short dark hair is swept to one side and her ethnicity is intentionally ambiguous, according to her developers, a team of researchers with the University of Southern California (USC) Institute for Creative Technologies. Some of the people who have interacted with her assume she is Asian; others conclude she has a completely different ethnicity. "People have come up and said that they're so thankful we paired them with someone of their race because it helped them connect," recalls Gale Lucas, a research assistant professor at USC.

How can we trust the networks?" They answered: "We know that a network is quite reliable when its inputs come from its training set. But these critical systems will have inputs corresponding to new, often unanticipated situations. There are numerous examples where a network gives poor responses for untrained inputs." David Lorge Parnas followed up on this discussion in his Letter to the Editor (Feb. We wish to point out that machine learning-based systems, including commercial ones performing safety critical tasks, can fail not only under "unanticipated situations" (noted by Lewis and Denning) or "when it encounters data radically different from its training set" (noted by Parnas), but also under normal situations, even on data that is extremely similar to its training set. The Apollo self-driving team confirmed "it might happen" because the system was "deep learning trained." Now, after a further investigation, we have found that in 24 of these 27 failed tests, the 10 random points ...

British Prime Minister Boris Johnson delivered his first speech in the Parliament on Thursday, promising to unleash a "new golden age for the United Kingdom" and leaving the European Union by the Oct. 31 deadline. Johnson, who formally took office on Wednesday, made a fiery speech in the parliament in a bid to turbocharge the effort to execute Brexit "for the purpose of uniting and re-energizing our great United Kingdom and making this country the greatest place on earth." He said that despite the looming Oct. 31 deadline, there's time to renegotiate with the European bloc and remains optimistic that a new deal can be reached. "This is the first day of a new approach which will start with our departure from the European Union on October 31 ... beginning new golden age for the United Kingdom." "This is the first day of a new approach which will start with our departure from the European Union on October 31," Johnson said, adding that it will mark the beginning of a "new golden age for the United Kingdom." Johnson also assured EU citizens currently living in the country that they would have "absolute certainty" of their right to live and remain in the country after Brexit.

Mitsubishi Fuso Truck and Bus Corp. said Wednesday that it will launch a heavy-duty truck featuring so-called Level 2 automated driving technologies in autumn. The autonomous technologies to be introduced for the Super Great truck allow steering, accelerator and brakes to be controlled by the vehicle, the automaker said. Mitsubishi Fuso, a unit of Germany's Daimler AG, aims to achieve Level 4, which provides for automated driving in limited areas, a company official said. It appears hard to benefit from the introduction of Level 3 technologies that require people to intervene in driving operations when necessary, the official said.

NAGOYA - Toyota Motor Corp. said Thursday it will set up a joint venture with Chinese ride-hailing giant Didi Chuxing Technology Co. and invest a total of ¥64.8 billion ($600 million) in Didi and the new venture, as part of efforts to expand its business in China. The venture, to be set up as early as this fall, will offer ride-hailing drivers a range of services that include vehicle maintenance, insurance and financing. GAC Toyota Motor Co., a venture established by Toyota and China's Guangzhou Automobile Group Co., will also join the project, through which Toyota aims to promote the use of electric vehicles suitable for future mobility services in China -- the world's biggest auto market. Toyota and Didi have already cooperated on leasing vehicles to ride-hailing drivers since last year, as well as in the e-Palette project to develop electric and autonomous vehicles that can be used as mobile stores. Inc. have joined the project.

The UK's forecasts for solar power generation have become far more accurate through the use of artificial intelligence, in a development that could lower energy bills and carbon emissions. The country's energy system is becoming more reliant sources of electricity with a variable output. Renewables like wind and solar, which depend on the weather, provided 36 per cent of our electricity at the start of this year, up from 7 per cent in 2009. "The growth in solar was much, much more fast-paced than anyone anticipated," says …

When Carol Baker, a 76-year-old driver from Annapolis, Maryland, gets behind the wheel of her 2016 Buick Enclave, her phone automatically connects to the car. She uses the Bluetooth technology to call friends and change the radio station without taking her eyes off the road. "It doesn't always understand what I'm saying," she says. "That can be a little frustrating." But audio commands and touchscreens in cars are more than frustrating for older drivers -- they can be downright dangerous.

A technology recruiting firm is having such a hard time finding artificial-intelligence professionals that it is offering a training program that covers the subject, with tuition costs covered if they agree to work for a client company. Modis Inc., a subsidiary of Switzerland-based global staffing company Adecco Group AG, this spring began testing a program in the U.S. that offers courses on topics including machine learning, some of which are open to people with little or no background in computer science.